class_docstr: Keras callback which updates pruning wrappers with the optimizer step.
  
  This callback must be used when training a model which needs to be pruned. Not
  doing so will throw an error.
  
  Example:
  
  ```python
  model.fit(x, y,
      callbacks=[UpdatePruningStep()])
  ```
class_docstr_tok: ["Keras","callback","which","updates","pruning","wrappers","with","the","optimizer","step",".","This","callback","must","be","used","when","training","a","model","which","needs","to","be","pruned",".","Not","doing","so","will","throw","an","error",".","Example",":","``","`","python","model.fit","(","x",",","y",",","callbacks=","[","UpdatePruningStep","(",")","]",")","``","`"]
code: def __init__(self):
      super(UpdatePruningStep, self).__init__()
      self.prunable_layers = []
  
file_path: model-optimization/tensorflow_model_optimization/python/core/sparsity/keras/pruning_callbacks.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import six
  import tensorflow
  from tensorflow_model_optimization.python.core.keras import compat
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_wrapper
label_desc: Use image node_id 1 to create a new UpdatePruningStep object from inherited base classes: callbacks with example: obj = UpdatePruningStep()